Junior Professional in AI and Data Science

Location: Noordwijk

Overview  This post is part of ESA’s Junior Professional Programme. We are looking for enthusiastic candidates with up to 2–3 years of relevant professional experience after their Master’s degree to join ESA for a four-year assignment. During this time, you will be actively working and learning on the job and will benefit from mobility and developmental opportunities that will prepare you for a successful career ject to performance, the intention is to offer an indefinite contract starting at the end of the four years.
The selection process for the 2025 cohort will take place in Spring 2025, with a projected start date in October or November 2025. Recruitment will take place at the A1 grade. At the end of the fourth year, if offered an indefinite contract, you will be upgraded to the A2 grade.

Location:

ESTEC, Noordwijk, Netherlands or other site, as required. Developmental assignments may entail a temporary relocation to another ESA establishment or location.
Description  The Future Engineering Division, in support of programme directorates, is responsible for developing and providing the right engineering expertise, tools, methods and standards for the development of future projects. The Division’s AI and Data Science Section leads the Agency’s centre of excellence for artificial intelligence (AI). The Section supports the development and exploitation of future space missions focusing on AI technologies and techniques, development and verification methods for AI systems, data science technologies and development methods, identification of future applications of AI, and monitoring evolutions of advanced technologies (such as quantum computing) to explore their suitability for space applications.
Duties   As a Junior Professional, demonstrate the feasibility and advantages of applying artificial intelligence technologies in space systems, focusing on one or more topics:
Onboard autonomy: implementing frugal AI solutions to increase autonomy of spacecraft, rovers and robots, addressing robustness, uncertainty control and mitigation while considering onboard deployment limitations.
Mission design and engineering: developing AI assistants to support the development of space missions throughout their lifecycle, ensuring compliance with high standards.
Insights from mission data: developing, adapting and deploying AI techniques in space assets to support onboard data analysis, minimising time to insights and reducing downlink of large data volumes.
You will use existing laboratory facilities, and potentially the ESA Space High-Performance Computer, to demonstrate technologies, and will actively seek promising application areas and provide demonstration testbeds and benchmarks for AI techniques and applications.
Development programme  In addition to daily work, you will participate in an extensive learning and development programme. From day one, you will learn on the job and benefit from tailored development opportunities, including participation in technical and key skills training courses.
There is a mobility component to the Junior Professional Programme that can include internal rotations to another team within ESA, external secondments outside of ESA, or a combination of both. Internal rotations boost professional experience and knowledge of the European Space Agency, while external secondments boost experience in the European space sector.
As part of the mobility component, you may have the opportunity to develop AI competencies in an industrial setting or at another ESA team.
This programme represents a significant investment by ESA in your development and is designed to provide you with the knowledge and skills for a career  can expect to develop professionally, learn from ESA experts and contribute to ESA activities.
Technical competencies   

Experience with artificial intelligence and machine learning frameworks

Experience with Big Data frameworks (data warehouse and data lake technologies)
Knowledge of several AI techniques and technologies such as supervised, unsupervised and reinforcement learning, model compression, transfer learning, natural language processing, large language models,…